For instance, the slope may be different for males and females, where gender is a predictor of the slope. But there is no variation in the slope within gender - that would imply a zero residual variance. Significance of a slope variance is often not found without covariates, while the slope still varies as a function of covariates when they are added.

I would like to analyze trajectory of elderly depressive symptoms over 6 years. Add to this, I would like to test if the trajectory influences on suicide ideation at 6th wave. In my data, suicide ideation is binary variable which was measured with yes or no question. In this case, do I have to apply logistic regression analysis in order to add suicide ideation variable as the outcome of depressive symptom trajectory? Is there any method for it?